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1.
Comput Biol Med ; 155: 106618, 2023 03.
Article in English | MEDLINE | ID: mdl-36774893

ABSTRACT

The ongoing COVID-19 pandemic is leading to the discovery of hundreds of novel SARS-CoV-2 variants daily. While most variants do not impact the course of the pandemic, some variants pose an increased risk when the acquired mutations allow better evasion of antibody neutralisation or increased transmissibility. Early detection of such high-risk variants (HRVs) is paramount for the proper management of the pandemic. However, experimental assays to determine immune evasion and transmissibility characteristics of new variants are resource-intensive and time-consuming, potentially leading to delays in appropriate responses by decision makers. Presented herein is a novel in silico approach combining spike (S) protein structure modelling and large protein transformer language models on S protein sequences to accurately rank SARS-CoV-2 variants for immune escape and fitness potential. Both metrics were experimentally validated using in vitro pseudovirus-based neutralisation test and binding assays and were subsequently combined to explore the changing landscape of the pandemic and to create an automated Early Warning System (EWS) capable of evaluating new variants in minutes and risk-monitoring variant lineages in near real-time. The system accurately pinpoints the putatively dangerous variants by selecting on average less than 0.3% of the novel variants each week. The EWS flagged all 16 variants designated by the World Health Organization (WHO) as variants of interest (VOIs) if applicable or variants of concern (VOCs) otherwise with an average lead time of more than one and a half months ahead of their designation as such.


Subject(s)
COVID-19 , SARS-CoV-2 , Humans , Pandemics , Benchmarking , Mutation
2.
Cell Rep ; 42(8): 112888, 2023 08 29.
Article in English | MEDLINE | ID: mdl-37527039

ABSTRACT

Evolution of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant has led to the emergence of sublineages with different patterns of neutralizing antibody evasion. We report that Omicron BA.4/BA.5 breakthrough infection of individuals immunized with SARS-CoV-2 wild-type-strain-based mRNA vaccines results in a boost of Omicron BA.4.6, BF.7, BQ.1.1, and BA.2.75 neutralization but does not efficiently boost BA.2.75.2, XBB, or XBB.1.5 neutralization. In silico analyses showed that the Omicron spike glycoprotein lost most neutralizing B cell epitopes, especially in sublineages BA.2.75.2, XBB, and XBB.1.5. In contrast, T cell epitopes are conserved across variants including XBB.1.5. T cell responses of mRNA-vaccinated, SARS-CoV-2-naive individuals against the wild-type strain, Omicron BA.1, and BA.4/BA.5 were comparable, suggesting that T cell immunity against recent sublineages including XBB.1.5 may remain largely unaffected. While some Omicron sublineages effectively evade B cell immunity, spike-protein-specific T cell immunity, due to the nature of polymorphic cell-mediated immune responses, may continue to contribute to prevention/limitation of severe COVID-19 manifestation.


Subject(s)
COVID-19 , T-Lymphocytes , Humans , Spike Glycoprotein, Coronavirus/genetics , SARS-CoV-2 , Antibodies, Neutralizing , Antibodies, Viral
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